Triple
T60173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathy Hochul |
E1192
|
entity |
| Predicate | termStartAsLieutenantGovernor |
P1814
|
FINISHED |
| Object | 2015-01-01 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2015-01-01 | Statement: [Kathy Hochul, termStartAsLieutenantGovernor, 2015-01-01]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termStartAsLieutenantGovernor Context triple: [Kathy Hochul, termStartAsLieutenantGovernor, 2015-01-01]
-
A.
hasLieutenantGovernor
Indicates that one entity serves as the lieutenant governor of another entity (typically a state, province, or territory).
-
B.
officeHolderStartTime
chosen
Indicates the date and time at which an individual begins holding a particular office or position.
-
C.
vicePresidentialTermEnd
Indicates the date or point in time when an individual's service in a specific vice presidential term comes to an end.
-
D.
governorTitle
Indicates the official title or designation held by a person serving as a governor.
-
E.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a251a1b8ac8190b44be4c3c41e5681 |
completed | Feb. 28, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69a24ea0bec48190b2af1fb287e9e692 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.